Vision-Inertial Navigation Systems (VINS) combine information from camera images (vision aiding) with information from inertial sensors (inertial aiding) to determine a vehicle's position, velocity and attitude. These systems provide a promising alternative to traditional GPS-INS systems, which are vulnerable to interference and jamming. Existing VINS can be separated into two categories: 1) systems that operate without pre-existing maps, such as optical flow, visual odometry and Simultaneous Localization and Mapping (SLAM) systems; and 2) systems that compare pre-existing maps to real-time imagery. The present disclosure refers to the latter type.
A key limitation of existing VINS is that they require clear, unobstructed views of environments that contain landmarks suitable for navigation purposes. Consequently, for airborne applications, during a time period while a vehicle with VINS is passing over cloud cover or featureless terrain (e.g., water), navigation errors increase over time without vision aiding (e.g., referred to as free-inertial error growth). Therefore, when the vehicle again reaches a suitably visible environment (e.g., clouds cleared or landfall made), the VINS has to re-localize itself by performing a search over a large area. Such a search involves comparing a real-time image from an onboard camera to a large area on a pre-existing map stored in the VINS. Depending on the length of time that the VINS has traveled during the outage period, and the quality of the sensor information provided by the vehicle's Inertial Measurement Unit (IMU), the map area that must be searched can be exceptionally large (e.g., up to thousands of square kilometers). As such, a significant problem that arises with existing VINS is that the process of searching such a large area of the map requires a substantial amount of computing resources. Consequently, such a search can take up a significant amount of time for an onboard processor to complete, which is an impractical result especially for airborne applications. Therefore, the need exists for a technique that can be utilized to significantly reduce the map area that must be searched by a VINS after an outage period has occurred, and thus enable the VINS to substantially reduce the recovery period and processing time required after experiencing a significant period of free-inertial drift.
For the reasons stated above and for other reasons stated below which will become apparent to those skilled in the art upon reading and understanding the specification, there is a need in the art for methods for reducing the map search area requirements in a vision-aided navigation system.